Output

Academic license - for non-commercial use only
Optimize a model with 2 rows, 2 columns and 2 nonzeros
Model has 1 quadratic constraint
Coefficient statistics:
  Matrix range     [1e+00, 1e+00]
  QMatrix range    [1e+00, 1e+00]
  Objective range  [0e+00, 0e+00]
  Bounds range     [0e+00, 0e+00]
  RHS range        [1e+00, 2e+00]
Presolve removed 2 rows and 2 columns
Presolve time: 0.00s
Presolve: All rows and columns removed

Barrier solved model in 0 iterations and 0.00 seconds
Optimal objective 0.00000000e+00
13
Freed default Gurobi environment

soc3.py

#!/usr/bin/python

from gurobipy import *

# Create a new model
m = Model("soc3")

# Create variables
x = m.addVar(name="x") # x >= 0 by default
y = m.addVar(name="y")

# Set objective: x
obj = 0.0*x
m.setObjective(obj, GRB.MINIMIZE)

# Add constraint: y >= 2
m.addConstr(y >= 2, "c0")

# Add constraint: x <= 1
m.addConstr(x <= 1, "c1")

# Add constraint: y^2 <= x^2 # x >= 0 implicitly
m.addQConstr(y*y <= x*x, "c2")

m.optimize()

print(m.status)